Short description: PhD defence Florian Arnold - Faculty of Business and Economics

Abstract

Routing is a core activity in logistics and involves the transportation of goods from one place to another. Especially with the rise of e-commerce shopping, an increasing number of people order products online and have them delivered as parcels at home. These delivery routes should be planned as efficiently as possible to safe costs, and reduce emissions. On the other hand, the planning of delivery routes is usually interconnected with other decisions in the supply chain: where should the warehouses be located (from where to deliver), and how many goods should be stored in the warehouses (are there sufficient goods to deliver).

The algorithmic planning of delivery routes, let alone its interplay with other activities, is a difficult problem in the field of Operations Research. For the delivery of goods to 60 customers, the number of possible delivery routes is already larger than the number of observable atoms in the universe. Therefore, routing is usually tackled with heuristics, which do not necessarily aim at finding the best routing plan, but rather at finding one that is good enough in a short time.

In this work, I develop a highly-efficient routing heuristic that is based on two principles: improve a routing plan by making many small changes in a very short time (local search), and gain insights into the structure of routing problems to guide this change process (problem knowledge). The resulting heuristic is among the most efficient ones in literature and can tackle the largest existing problems. From a practical side, I use this heuristic to study routing in the context of integrated logistics. How should inventory management and routing be combined to maximize the overall efficiency, and where should warehouses be located. Finally, I discuss the value of routing algorithms with a practical case study that demonstrates the benefits of delivering parcels in Antwerp via cargo bikes.